The Capybara series is a collection of datasets and models made by fine-tuning on data created by Nous, mostly in-house.
V1.9 uses unalignment techniques for more consistent and dynamic control. It also leverages a significantly better foundation model, Mistral 7B.
Sample code and API for Capybara 7B
OpenRouter normalizes requests and responses across providers for you.
To get started, you can use Capybara 7B via API like this:
fetch("https://openrouter.ai/api/v1/chat/completions",{ method:"POST", headers:{"Authorization":`Bearer ${OPENROUTER_API_KEY}`,"HTTP-Referer":`${YOUR_SITE_URL}`,// Optional, for including your app on openrouter.ai rankings."X-Title":`${YOUR_SITE_NAME}`,// Optional. Shows in rankings on openrouter.ai."Content-Type":"application/json"}, body:JSON.stringify({"model":"nousresearch/nous-capybara-7b","messages":[{"role":"user","content":"What is the meaning of life?"},],})});
You can also use OpenRouter with OpenAI's client API:
import OpenAI from"openai"const openai =newOpenAI({ baseURL:"https://openrouter.ai/api/v1", apiKey: $OPENROUTER_API_KEY, defaultHeaders:{"HTTP-Referer": $YOUR_SITE_URL,// Optional, for including your app on openrouter.ai rankings."X-Title": $YOUR_SITE_NAME,// Optional. Shows in rankings on openrouter.ai.}})asyncfunctionmain(){const completion =await openai.chat.completions.create({ model:"nousresearch/nous-capybara-7b", messages:[{ role:"user", content:"Say this is a test"}],})console.log(completion.choices[0].message)}main()
See the Request docs for all possible parameters, and Parameters for recommended values.